scholarly journals Ecological boundary detection using Bayesian areal wombling

Ecology ◽  
2010 ◽  
Vol 91 (12) ◽  
pp. 3448-3455 ◽  
Author(s):  
Matthew C. Fitzpatrick ◽  
Evan L. Preisser ◽  
Adam Porter ◽  
Joseph Elkinton ◽  
Lance A. Waller ◽  
...  
Keyword(s):  
Boundary Detection ◽  
Ecological Boundary

Video Shot Boundary Detection � Comparision of Color Histogram and Gist Method

2012 ◽  
Vol 1 (1) ◽  
pp. 11-19
Author(s):  
P. Swati Sowjanya ◽  
Ravi Mishra
Keyword(s):  
Boundary Detection ◽  
Color Histogram ◽  
Shot Boundary Detection ◽  
Video Shot ◽  
Shot Boundary

Boundary Detection Using Open Spline Curve Based on Mumford-Shah Model

2009 ◽  
Vol 35 (2) ◽  
pp. 132-136 ◽  
Author(s):  
Xiao-Mao LI ◽  
Lin-Lin ZHU ◽  
Yan-Dong TANG
Keyword(s):  
Boundary Detection ◽  
Spline Curve

An Efficient Shot Boundary Detection Using Data-cube Searching Technique

2020 ◽  
Vol 13 (4) ◽  
pp. 798-807
Author(s):  
J. Kavitha ◽  
P. Arockia Jansi Rani ◽  
P. Mohamed Fathimal ◽  
Asha Paul
Keyword(s):  
Texture Features ◽  
Boundary Detection ◽  
Data Cube ◽  
Multimedia Data ◽  
Shot Boundary Detection ◽  
Gradual Transition ◽  
Detection Rates ◽  
Effective Manner ◽  
Shot Boundary ◽  
Shot Transitions

Background:: In the internet era, there is a prime need to access and manage the huge volume of multimedia data in an effective manner. Shot is a sequence of frames captured by a single camera in an uninterrupted space and time. Shot detection is suitable for various applications such that video browsing, video indexing, content based video retrieval and video summarization. Objective:: To detect the shot transitions in the video within a short duration. It compares the visual features of frames like correlation, histogram and texture features only in the candidate region frames instead of comparing the full frames in the video file. Methods: This paper analyses candidate frames by searching the values of frame features which matches with the abrupt detector followed by the correct cut transition frame with in the datacube recursively until it detects the correct transition frame. If they are matched with the gradual detector, then it will give the gradual transition ranges, otherwise the algorithm will compare the frames within the next datacube to detect shot transition. Results:: The total average detection rates of all transitions computed in the proposed Data-cube Search Based Shot Boundary Detection technique are 92.06 for precision, 96.92 for recall and 93.94 for f1 measure and the maximum accurate detection rate. Conclusion:: Proposed method for shot transitions uses correlation value for searching procedure with less computation time than the existing methods which compares every single frame and uses multi features such as color, edge, motion and texture features in wavelet domain.

Accurate Boundary Detection and Refinement for Continuous Objects in IoT Sensing Networks

2019 ◽  
Vol 57 (6) ◽  
pp. 93-99 ◽  
Author(s):  
Zhangbing Zhou ◽  
Yaqiang Zhang ◽  
Xuefang Yi ◽  
Chao Chen ◽  
Haodi Ping
Keyword(s):  
Boundary Detection ◽  
Continuous Objects

Automated grain boundary detection by CASRG

2006 ◽  
Vol 28 (3) ◽  
pp. 363-375 ◽  
Author(s):  
Kingshuk Roy Choudhury ◽  
Patrick A. Meere ◽  
Kieran F. Mulchrone
Keyword(s):  
Grain Boundary ◽  
Boundary Detection ◽  
Grain Boundary Detection

Multiagent boundary detection system: a way to parallel image processing

1997 ◽  
Author(s):  
Pascal Ballet ◽  
Vincent Rodin ◽  
Jacques Tisseau
Keyword(s):  
Image Processing ◽  
Detection System ◽  
Boundary Detection ◽  
System A ◽  
Parallel Image Processing ◽  
Parallel Image
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